Selected article for: "estimation sequencing and length estimation"

Author: Maximilian Krause; Adnan M. Niazi; Kornel Labun; Yamila N. Torres Cleuren; Florian S. Müller; Eivind Valen
Title: tailfindr: Alignment-free poly(A) length measurement for Oxford Nanopore RNA and DNA sequencing
  • Document date: 2019_3_25
  • ID: cq7g8azh_12
    Snippet: In comparison to recent short-read sequencing-based strategies to measure poly(A) tails, methods using ONT sequencing are currently less precise. Short-read sequencing approaches promise poly(A) measurements with just a few bases of deviation due to cyclic incorporation of nucleotides and integration of the fluorescence signal of multiple molecules towards one single basecall [20, [25] [26] [27] [28] . In contrast, ONT long-read sequencing measur.....
    Document: In comparison to recent short-read sequencing-based strategies to measure poly(A) tails, methods using ONT sequencing are currently less precise. Short-read sequencing approaches promise poly(A) measurements with just a few bases of deviation due to cyclic incorporation of nucleotides and integration of the fluorescence signal of multiple molecules towards one single basecall [20, [25] [26] [27] [28] . In contrast, ONT long-read sequencing measures individual single-stranded molecules, and single nucleotide changes are detected based on subtle changes in measured current levels. More importantly, the raw signal for ONT sequencing does not change over a homopolymeric region, making single-event detection almost impossible. Thus, ONT poly(A) length estimation relies on normalisation rather variable data taken from single-molecule measurements. Most of the variation observed in tailfindr poly(A) estimation thus comes from the sequencing process. However, the sequencing chemistry as well as the properties of the motor protein are under constant development. It is thus conceivable that in the near future an increase in speed and robustness of translocation rates can be observed, which will have a positive impact on poly(A) tail estimation [35] .

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